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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Future-proof production scheduling and control</dc:title><dc:creator>Urgo,	Marcello	(Avtor)
	</dc:creator><dc:creator>Lanza,	Gisela	(Avtor)
	</dc:creator><dc:creator>Vrabič,	Rok	(Avtor)
	</dc:creator><dc:creator>Gyulai,	Dávid	(Avtor)
	</dc:creator><dc:subject>production scheduling</dc:subject><dc:subject>production control</dc:subject><dc:subject>digital twin</dc:subject><dc:description>Traditional production scheduling and control are increasingly inadequate in light of the rapid evolution of manufacturing technology, the growing impact of unforeseen disruptions, and the generally increasing complexity of production. A framework for future-proof production scheduling and control is introduced to close this gap, providing a comprehensive overview of future requirements and the necessary technologies and approaches. Robust decision criteria are derived, explained and filled with major recent advances in production scheduling and control, digital twins, artificial intelligence, and knowledge formalisation. Emerging trends are discussed, and an outlook for future research and decision-making is derived.</dc:description><dc:date>2025</dc:date><dc:date>2026-01-19 11:04:21</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>178121</dc:identifier><dc:identifier>UDK: 62:004.896</dc:identifier><dc:identifier>ISSN pri članku: 1726-0604</dc:identifier><dc:identifier>DOI: 10.1016/j.cirp.2025.04.095</dc:identifier><dc:identifier>COBISS_ID: 264116739</dc:identifier><dc:language>sl</dc:language></metadata>
